Project Summary/Abstract Neuropathic pain, which originates from tissue damage in the nervous system, afflicts a substantial number of Americans by impairing daily functions, hindering work performance, and exacerbating quality of life. The canonical treatments for neuropathic pain are opioid-based analgesics, which are pharmacologically non- specific and can cause severe side effects such as respiratory depression, physical dependence, and addiction. Neuropathic pain is facilitated by cellular and molecular changes in the spinal cord. However, these changes manifest in a variety of cell types and the cell-specific changes underlying neuropathic pain are not well understood. Furthermore, spinal pain circuits are structurally and functionally divergent, in that pain-related spinal neurons project to different brain areas. This circuit divergence is thought to be responsible for different components of pain: somatosensory detection and aversive (unpleasant) affiliation. Single-cell RNA sequencing (scRNAseq) approaches can characterize the cellular makeup of heterogeneous tissues. Alternatively, fluorescence-activated cell sorting (FACS) can be used to isolate and characterize unique cell types through bulk RNA sequencing. These approaches can also be used to detect changes in gene expression following pathological perturbation. In preliminary studies, I used the scRNAseq approach known as Drop-seq to detect the diverse cell types found in the spinal cord. Additionally, I sorted backlabeled pain- projecting neurons to test the feasibility of isolating unique circuit-specific pain-projecting neurons. In this proposal, I hypothesize that scRNAseq can be used to identify transcriptional changes underlying chronic pain with single-cell resolution using a nerve injury model of neuropathic pain. Further, I hypothesize that neuronal tracing techniques used in parallel with bulk RNAseq can elucidate transcriptional differences underlying structurally and functionally divergent spinal pain circuits. In pilot experiments, I sequenced a low number of single-cell spinal transcriptomes from injured and uninjured animals. By referencing published work, I verified the identity of principle spinal cell types and was able to detect canonical changes in gene expression as a response to nerve injury. Thus, by sequencing more cells I will characterize the cellular heterogeneity of the spinal cord and identify cell-specific transcriptional changes that facilitate pain phenotypes. In addition, to characterize nociceptive projection neurons, I will backlabel spinal neurons that project to different brain structures with fluorescent tracers and use FACS to isolate target- specific cells for bulk RNAseq. Comparing transcriptomes from nociceptive neurons that project to different brain areas may reveal molecular differences in pain pathways at the level of the spinal cord. The cell-specific characterizations generated from these experiments will be used to identify novel cell markers and potential drug targets for alternative analgesics.